code: def _get_rbf_kernel(num_samples: int, dim: int) -> ScaleKernel:
      return ScaleKernel(
          base_kernel=RBFKernel(
              ard_num_dims=dim, batch_shape=torch.Size([num_samples])
          ),
          batch_shape=torch.Size([num_samples]),
      )
  
file_path: Ax/ax/models/torch/fully_bayesian_model_utils.py
imports: from typing import Any, Dict, List, Optional, Tuple
  import pyro
  import torch
  from ax.models.torch.botorch_defaults import _get_model
  from botorch.models.gp_regression import MIN_INFERRED_NOISE_LEVEL
  from botorch.models.gpytorch import GPyTorchModel
  from botorch.models.model_list_gp_regression import ModelListGP
  from gpytorch.kernels import MaternKernel, RBFKernel, ScaleKernel
  from torch import Tensor
label_desc: Use image node_id 1 for calling a global function with example usage: _get_rbf_kernel(num_samples, dim) and returns: ScaleKernel